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Showing posts with the label variable

### Factor Analysis Principal Components Analysis

Factor analysis (FA)  is a statistical method of reducing a large set of data to a smaller set by identifying patterns in the data that have common characteristics. Factor analysis is sometimes called data reduction or dimension reduction. The original numerical values in the data set are observed variables (also called manifest variables)  such as the items in a large survey or test. Factor analysis may find patterns characterized by a shared statistical relationship representing a factor, which is also called a dimension . A researcher examines the content of the items linked to this factor and chooses a factor label such as verbal skills for related items on an intelligence test. The factors may be treated as variables in additional research. These are secondary variables. Because they are created from the observed variables, they are considered latent variables. For example, if 5 items on a personality test are associated with one factor labeled "agreeableness" then agr

### Continuous variables in behavioral research

Continuous variable . A variable having a wide range of numerical values, such as intelligence, achievement, and personality variables. Example : Scores on a Big Five test of personality are often reported as T-Scores for each of the five scales. Most people obtain scores in the range of 40 to 60 but it is possible to obtain lower and higher scores. The point of the example is that the scores are continuous and cover a wide range.  Researchers can group people based on their scores using groups labels like "high" and "low" perhaps by deciding that the median would be the score to separate high and low scores. Changing the continuous variable results in the formation of a grouping variable or categorical variable. Example 2 : Age is a continuous variable beginning at birth and continuing to death. Researchers can group people by age and create a grouping or categorical value. Learn More about variables in Creating Surveys on  AMAZON  or  GOOGLE Please check out m

### Confounding variables in behavioral research

A Confounding variable  is a variable that produces unexpected changes in the dependent variable and therefore interferes with interpreting the capacity of an independent variable   to produce or explain changes in a dependent variable . Example : During a study of anxiety that includes measures of anxiety and stress, some participants watch a documentary about the treatment of anxiety and some do not. Documentary-watching may confound the results if watching the program influenced the scores on the measures of anxiety and stress. Similarly, some participants may be exposed to a source of stress in their environment but others are not, which could interfere with interpreting the results. Learn More about research methods and variables in Creating Surveys on  AMAZON  or  GOOGLE Please check out my website     www.suttong.com    and see my books on    AMAZON         or   GOOGLE STORE Also, consider connecting with me on     FACEBOOK     Geoff W. Sutton         TWITTER    @Geoff.

### Categorical or Grouping variable in Behavioral Research

Categorical variables are those variables having two or more groups or levels such as sex, ethnicity, and religious group.  They may be called independent variables even though they are not true independent variables under experimental control. Categorical variables, also called grouping variables,  can be created from continuous variables . For example, researchers often obtain the age of their study participants. Age is a continuous variable but sometimes, researchers group ages together and compare how people of different age groups answer questions on a survey. Learn More in Creating Surveys on  AMAZON  or  GOOGLE Please check out my website     www.suttong.com    and see my books on    AMAZON         or   GOOGLE STORE Also, consider connecting with me on     FACEBOOK     Geoff W. Sutton         TWITTER    @Geoff.W.Sutton     You can read many published articles at no charge:   Academia    Geoff W Sutton       ResearchGate    Geoffrey W Sutton

### Independent Variable IV

Independent variable (IV) . The variable in a research study that a researcher manipulates to determine if another variable, the dependent variable , changes when the IV changes. Creating Surveys on AMAZON    or   GOOGLE  Worldwide Links to Connections Checkout My Website     www.suttong.com    See my Books    AMAZON             GOOGLE STORE   FOLLOW me on    FACEBOOK     Geoff W. Sutton          TWITTER    @Geoff.W.Sutton      PINTEREST    www.pinterest.com/GeoffWSutton   Read published articles:     Academia    Geoff W Sutton         ResearchGate    Geoffrey W Sutton

### Dependent Variable DV

Dependent variable (DV ). The variable in a research study that is expected to change when a researcher varies the level of an independent variable . Example: In a counseling study designed to help people forgive, forgiveness would be the DV and the survey used to measure forgiveness would be the Dependent Measure. Creating Surveys on AMAZON    or   GOOGLE  Worldwide Links to Connections   Checkout My Website     www.suttong.com    See my Books      AMAZON             GOOGLE STORE   JOIN me on      FACEBOOK     Geoff W. Sutton          TWITTER    @Geoff.W.Sutton      PINTEREST    www.pinterest.com/GeoffWSutton   Read many published articles:     Academia    Geoff W Sutton         ResearchGate    Geoffrey W Sutton

### ANCOVA in Counseling & Behavioral Research

ANCOVA ANCOVA is a procedure like ANOVA except researchers can study the effects of one or more independent variables on a dependent variable after adjusting for other variables, called covariates , which were not a primary focus of the study. The letter C in ANCOVA stands for covariate . There can be several covariates in a study. In testing for differences among groups experiencing different leadership styles, we could study the effects on employee satisfaction after adjusting for a covariate of years of employment. A key word in ANCOVA studies is adjusting . Analysts adjust the scores based on information about the covariate before testing for significant differences. Basic features of an ANCOVA: Independent or grouping Variable = 1 or more Dependent or criterion Variable = 1 Covariates = 1 or more An  F  test indicates significance overall and for specific effects or relationships. A commonly reported measure of effect size is eta squared. A  p  value reveals the probabilit

### Chi-Square

Chi-Square is a statistical test that can be used to analyze results from categorical variables. Categorical variables are variables that contain clearly different groups. The chi-square statistic is used with frequency data.  The chi-square value is reported with a probability ( p ) value indicating significance.  For example, we can use chi-square to test for an association between frequency of attendance at organizational meetings and age groups (category variable).  Common measures of effect size associated with chi-square analyses are Cramer’s V or the phi coefficient. Read more about Chi Square and other statistics in the following books. Applied Statistics: Concepts for Counselors on  AMAZON  or GOOGLE Creating Surveys on AMAZON     or   GOOGLE  Worldwide Links to Connections   Please check out my website     www.suttong.com    and see my books on    AMAZON        or  GOOGLE STORE Also, consider connecting with me on    FACEBOOK     Geoff W. Sutton         TWITTER    @Ge

### Regression Data Analysis

Regression is a statistical procedure used to predict values on a criterion variable from the knowledge of values obtained on a predictor variable. For example, an organization may use an employment screening test or survey that has been useful in the past to predict how well employees perform a particular type of job. The criterion variable is a continuous variable, meaning it can have a range of score values. Predictor variables may be either continuous or categorical variables. When there is only one predictor variable and one criterion variable, the procedure is known as simple regression .   Read more about regression in these books. Applied Statistics on AMAZON or GOOGLE Creating Surveys on AMAZON or GOOGLE Checkout My Page     www.suttong.com    My Books   AMAZON         and            GOOGLE STORE   FOLLOW me on    FACEBOOK     Geoff W. Sutton           X   @Geoff.W.Sutton      PINTEREST    www.pinterest.com/GeoffWSutton   Articles:    Academia